Editor’s Note: The following is a reader submission from our friend and longtime community member SPTSJUNKIE. Dating back to our previous home, he shared his annual draft analysis in FanPosts, and we’re happy to share his work this year and continue the tradition.
After an uneventful 2019 draft where our beloved Kings did not make a selection until the 40th pick, this year we have four draft picks, including picks #12 and #35 with plenty of rumors that McNair is actively exploring trades that could net us extra picks in any range.
Given the energy and enthusiasm I always have for the draft and my desire to not slowly go insane during quarantine and recreate the scenes from The Shining with my husband and puppy – I have completed my 7th annual draft projection models and created some detailed write ups on the top prospects based on deep dives into hours and hours of both scouting / watching video and diving deep into the model and other metrics via resources like Synergy Sports, Basketball Reference, Hoop Math, and more.
For those of you not familiar with my models or how draft projection models work – the short answer is that it’s letting computers do math that would take me years to look at everything from basic box score stats, advanced metrics (i.e., BPM, net rating), efficiency statistics (i.e., true shooting percentage), scouting variables (do scouts describe a player as a high IQ player or having a strong motor), combine measurements, and more to try to figure out what makes a college player more likely to be successful in the NBA and then applying those to this year’s class.
Because there are so many ways to approach the problem – I actually do 5 models every year.
- One that uses all players.
- One that only uses players drafted after 2010 to consider see if the game has evolved.
- One that looks at individual positions and tries to separate if there are differences in what makes a great PG versus a great SF.
- And two that also incorporate mock draft order (via ESPN) to see if the scouts rankings can make our predictions even better because they see things beyond the numbers
Of course, as I caution every year, these models are great and I learn a lot doing them. But no credible front office or analyst would simply use a model as their draft order. They are simply another tool to combine with what we see on film, our intuition, and outside factors (i.e., is he the type of player who can’t stay in shape, doesn’t love basketball, has severe anger issues, or gets into constant trouble off the court).
Additionally, models are based on performance data – they can’t tell if a coach badly misused a player, if a school had so much talent that a player’s skills were hidden, or if a team had no shooters and a player was triple teamed on every drive. So these models should serve as a point of discussion versus the final word that serves to shut down the conversation.
For me personally, I learn a lot from the types of variables the models use and how that relates to players – often helping me understand strengths and weaknesses. Additionally, if a player rates much higher or lower than expected – it makes me go review more film and revisit their performance data to try to understand why.
With that said, below are links to two different resources that I have put together for fellow Kings Herald readers. We are lining to both of these Google docs externally as picture compression can make the rankings hard to read and to keep all of the write ups together and easy to reference before and after the draft instead of spread across several articles:
SPTSJUNKIE’s 7th Annual Model and draft guide with model results, explanations of what metrics predicted success, full player writes ups, and thoughts on who we should draft.
Larger model rankings in Google Sheets with all 76 player projections and rankings across all 5 models that are explained in the first Google document.
Please click through to read and come back here to comment below. Which model do you think is most accurate? Any surprises or does this change how you think about certain prospects? Any additional prospects you would like to see more detailed write ups or statistical profiles on?
Follow @SPTSJUNKIE on Twitter.
Well there goes my afternoon…luckily don’t need to watch the Niners anymore anyway! Great work, this is amazing stuff : )
Great stuff as usual. Happy to see it come back here at TKH.
One question:
How does this impact your / your models’ view of other international players like Hayes, Avdija and Maladon, who played in much better leagues than Ball?
That’s a great question and the short answers is that it mostly does not and that’s something we need to consider qualitatively when looking at the projections and deciding how we value the players.
The dataset does have a few potential variations of strength of schedule in it and I tried to pick a proxy school that roughly matched the quality of the different leagues as the ABL and the Greek B League clearly are not as strong as some of the Euroleagues.
However, the models generally don’t end up using any of the SOS variations. I think it’s a bit of input bias as the players I gather the data and comb through the scouting reports on are players who are mostly projected to be drafted. If I used the entire database of players from good / bad teams and from D1, D2, and D3 – I assume the model would pick up on it very quickly. But the handful of D2 players scouts have championed have mostly been very good.
So based on the dataset or after the scouts have done their work identifying top players, then SOS typically isn’t a significant factor.
That said, a future enhancement for the model is going to be a better approach to overseas players. Most of the database is NCAA and the last couple of seasons really haven’t had a lot of top prospects from overseas (aside from Doncic who the model projected as a superstar).
Get it ready for Josh Giddey!
Great, thanks.
And one more question: when comparing this draft to previous ones, is it indeed a weak draft?
The projections mirror what I think people have observed – the draft is weak at the top. Even if we believe Wiseman’s 3 game sample is legitimate and his projections are not overstated – having the “best” player in all of the rankings in the 14-16 range is low. Especially given the switch from raw win shares to adjusted (just scaled the target variable up to 82 games, as this year in particular saw a number of young players make a leap, but in 62 games). So that 16 is more like a 15 in past years.
Typically there is at least one prospect pushing a projection in the 18-20 range. However, there are a lot of players who are rating as useful players. So this could easily be a draft without a lot of stand out stars or superstars, but that produces a lot of quality starters and bench players. It’s not hard to imagine a lot of guys like even drafted in the later lottery or first round like Vassell, Nesmith, Jalen Smith, and Maxey staking out 10 year careers, even if they have 0 all star appearances between them.
Glancing backwards, the last draft that looks a bit like this was 2017. All 5 models were a bit split on who the best players were. A lot of top scores in the 12-15 range. But even players in the later teens in the projections rated as solid starters / bench players. And with a couple of years behind us, Tatum might be the biggest star and he was drafted at 3 and then the next best players are a mix of Mitchell, Fox, and Bam. All very good, but two drafted later and Bam developed a lot. And then a lot of very solid players who look like they could have long careers including later drafted players like both Collins, Allen, Kennard, Morris, and Anunoby.
Incredible work, as always.
The models like Paul Reed. I like the models.
I’m taking 4/5 of the models loving Isaac Okoro as just more proof that the Kings should trade up and get him.
Excellent work as always, Chris – I’m glad this came over in the THK transition! I appreciate the level of detail and work you’ve put into this. We truly agree on most of our draft preferences, save that you’re silly high on Aaron Nesmith and I’m rightfully correct on Tyrese Maxey.
I am not sure I am quite as high on Okoro as the models – though they have a tendency to be right other than with slow PGs and old school big men. I think his efficiency, high free throw rate, and college impact at his age are all signs he has a good chance to make a real impact. Even without improving his shot, he could at least be another Winslow, which may not sound great, but Winslow was already becoming an elite defender before he started having issues staying healthy. And his upside is clearly very high. If he slipped to 12 I would be thrilled. And if we traded up and snagged him, I’d be happy as well.
And ha – I think my discussions of / defending Nesmith makes it seem like I am a bigger fan than I probably am. I see a solid starter with upside to be a plus starter and maybe more. I think there are higher upside players and I see his limitations as giving him a ceiling unless he truly has some outlier development. I just think we have burned so many draft assets that our asset base is low and simply adding more good players and building our asset base will be helpful and is how a lot of teams have built. I might be acting a little gun shy of swinging for the fences but adding a player whose value might become near-0 within 6 months.
With that said, I am fine with chasing upside as well. The new FO has a clean slate and a lot of potential approaches. I wouldn’t blink or sigh in frustration if McNair drafted Williams. I don’t “hate” him as a prospect like I did with JJ or see him as well below other options like Bagley over Doncic. So I really think it’s more a question of approach.
These are awesome.
I’d like to point out high high Haliburton is in these models and I’d also like to say TRADE UP FOR HALIBURTON IF HE IS AVAILABLE.
I’m now convinced. Poku at #12 or trade up for Haliburton. Make it so.
You and me both. If we cam out of this draft with Halliburton, that would be a fantastic start to the McNair era.
And if we traded a player for another pick and were able to get Poku on top of Halliburton (not exactly what you said I know), that would also be the perfect mix of picking up a pretty safe prospect and then taking a big swing. I love the idea of that.
Man you’re going to make me read a spreadsheet to understand your draft goodness? Piss on you Junkie. How dare you make me read?
I’ll crate a picture book version next year for any of the anti-readers. Jk. Happy you enjoyed it.
It was interesting what I did peruse so far. But it always is. Also: For the picture book I’m requesting pop ups and dinosaurs. That’s just the best, really.
One question: What makes you think this draft is comparable to 2017? Actually, nevermind. I think you explained it already. Maybe I’m just skeptical of that comp because of all the unknowns for 2020. It’s just going to be a weird draft, no matter what, this year.
Yeah, to be clear, not saying it’s exactly like 2017. That was just a similar year glancing at the overall scores of the top prospects versus the middle of the draft.
Some years the projections predict a few stars and a big drop off. Both this year and 2017 has a couple of lower ceiling stars and a robust middle of the draft.
Hopefully, since we have 4 picks that turns out to be accurate and it’s not like 2016 where it was a wasteland after the first few picks other than a couple of gems selected later.
That would be nice to get a break!
Thanks for the hard work. Interesting read.
McNair, meet SPTSJUNKIE
Always awesome! Just amazing and I learned a lot from reading through this. I had been sort of on the fence about Killian Hayes but the more that I read the more I think that if he’s available at 12 he’d be a smart pick. I also noticed that Givony has had Hayes going to the Kings at 12 and it does make me wonder if there’s some smoke there unless he goes higher which is clearly possible.
If Hayes is there at 12, I think we’d be lucky to get him, especially in a draft like this. Seems like at a minimum, he should be a solid SG with upside for more.
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